Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Pedestrian Attribute Recognition is a foundational computer vision task that provides essential supp...
Recent studies have observed that intermediate layers of foundation models often yield more discrimi...
Diffusion Transformers (DiTs) have emerged as the dominant architecture for high-quality image and v...
The preprint ecosystem has expanded rapidly over the past decade, fundamentally altering science com...
Background: Cardiovascular disease remains the leading cause of global morbidity and mortality. The ...
Natural evolution is high-dimensional; organisms adapt to many pressures at once, across substrates,...
Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling neural networ...
Look-Up Table based methods have emerged as a promising direction for efficient image restoration ta...
Federated learning (FL) in post-deployment settings must adapt to non-stationary data streams across...
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions based ...
Diffusion models have demonstrated remarkable success in image and video generation, yet their pract...
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions based ...
Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generati...
The optimization of complex medical appointment scheduling remains a significant operational challen...
Meta-learning methods perform well on new within-distribution tasks but often fail when adapting to ...
Crafting adversarial examples can be formulated as an optimization problem. While sign-based optimiz...
Heavy-tailed stochastic gradient noise, commonly observed in transformer models, can destabilize the...
Object detectors achieve strong performance under nominal imaging conditions but can fail silently w...
Objective: Electronic Health Record (EHR)-based trial emulation can support translation of randomize...
Diffusion Transformers (DiTs) have achieved state-of-the-art performance in image and video generati...
Medical vision-language models (VLMs) are strong zero-shot recognizers for medical imaging, but thei...